NIOSH-IREP technical documentation

June 18, 2002

Figure 2. ERR/Sv estimates (at the upper 99" percentile of the credibility distribution) for
basal cell carcinoma (triangle) and for miscellaneous cancer (X) models, from NCI (2002), for

(a) males and (b) females.

(a) Males

100.0 J —*— BCC, Exposure age=20 —<— Misc, Exposure ag
—a’ —BCC, Exposure age=30 —X = Misc, Exposure age=30
= & - BCC, Exposure age=40 —X — Misc, Exp. age=40

i “ie "he i “ik x x _¥

Upper 99th percentile of ERR/Sv

=20

10.0 4
bet te
coe Se ee ae
7 ~~ Se

25 30 35 40 45 50 55 60 65
Age at diagnosis

(b) Females

——&— BCC, Exposure age=20 —< Misc, Exposure age=20
100.0 —A- ‘BCC, Exposure age=30 —>< ‘Misc, Exposure age>=30

10.0 +

;
ta Se ee See |
donk - ee -
1.0 + + + + + + + +

Upper 99th percentile of ERR/Sv

- A ~ BCC, Exposure age=35 =A - BCC, Exposure age=40

25 30 35 40 45 50 55 60 65
Age at diagnosis

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70

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NIOSH-IREP technical documentation June 18, 2002

proportion of these would proceed to invasive malignant neoplasms without intervention, and it is
impossible to determine this at the level of the individual claimant. A policy consistently used in
NIOSH-IREP is to provide the benefit of doubt to the claimant, and to assume that a carcinoma in situ
is a malignant neoplasm. No distinction is made among the sites at which the CIS might develop with
regard to this policy. Therefore, within NIOSH-IREP, CIS will be treated as a malignant neoplasm of
the specified site.

Cancers identified by their secondary sites (sites to which a malignant cancer has spread), when
the primary site is unknown, raise another issue for the application of IREP. This situation will most
commonly arise when death certificate information is the primary source of a cancer diagnosis. It is
accepted in medicine that cancer-causing agents such as ionizing radiation produce primary cancers.
This means, in a case in which the primary site of cancer is unknown, the primary site must be
established by inference to estimate probability of causation.

An evaluation of the relationship between primary and secondary cancer sites using the National
Center for Health Statistics (NCHS) Mortality Database for years 1995-1997 was used to infer the
primary site when only the site of metastasis is known. Because national cancer incidence databases
(e.g., the National Cancer Institute’s Surveillance, Epidemiology and End Results program) do not
contain information about sites of metastasis, the NCHS database was considered the best available
data source to assign the primary site(s) most likely to have caused the spread of cancer to a known
secondary site. For each secondary cancer, the set of primary cancers producing approximately 75%

of that secondary cancer among the U.S. population was identified (males and females were considered

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Table 2. Cancer sites as source for excess relative risk (ERR) per Sv coefficients for risk
models in NIOSH-IREP, and cancer group to which model should be applied.

Cancer models in NIOSH-IREP

Cancer site used as

ICD - codes of

source of ERR/SV background rates
(ICD-9 code)
Oral Cavity and Pharynx (140-149) 140-149 140-149
Esophagus (150) 150 150
Stomach (151) 151 151
Colon (153) 153 153
Rectum (154) 154 154
All digestive (150-159) 150-159 150-159
Liver (155.0) 155.0 155.0
Gallbladder (155.1, 156) . 155.1, 156 155.1, 156
Pancreas (157) 157 157
Trachea, Bronchus and Lung (162) 162 162

Other respiratory (nasal cavity, larynx and
other, 160, 161, 163-165)

160, 161, 163-165

160, 161, 163-165

Bone (170) 170, 171, 175, 190, 170
194, 195
Connective tissue (171) 170, 171, 175, 190, 171
194, 195
Malignant melanoma (172) 173 (basal cell 172
carcinoma only)
Non-melanoma skin (173) -basal cell 173 (basal cell 173 (all combined)
carcinoma carcinoma only)
Non-melanoma skin (173)-non basal cell | 173 (non-basal cell 173 (all combined)
carcinoma carcinoma only)
Breast-female (174) 174 174
Breast-male (175) 174 175

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approach that was considered was the use of the miscellaneous cancer model, which includes
male breast cancer incident cases from the Japanese atomic bomb survivor cohort. In the
absence of scientific information to determine which of two or more alternative methods should
be used, a consistent policy throughout the development of the HHS methods for determining
probability of causation under EEOICPA has been to use the approach that is most favorable
to the claimant. The female breast is considered among the most radiosensitive tissues in the
body (Boice et al. 1996); however, sensitivity of the breast decreases greatly with increasing
age at exposure. Therefore, it is not immediately clear which source of risk coefficients
provides the most claimant-favorable estimate of probability of causation. Examination of the
upper 99" percentile ERR/Sv estimates for both models (Fig. 3) shows that the use of the
female breast cancer model provides the most claimant-favorable estimates, at most
combinations of exposure and diagnosis ages.

Within NIOSH-IREP, therefore, for the male breast cancer model, ERR per Sv
coefficients from female breast cancer models were modified by the background incidence
rates for male breast cancer in the U.S. and Japan (Parkin et al. 1997; NCI 2000, 2002).

There is no data to support the use of any particular risk transfer model between the Japanese
and U.S. populations. In the absence of such information, the approach developed for all
cancers other than female breast and stomach was employed in NIOSH-IREP. This transfer
function is trapezoidal, which equally weights additive and multiplicative transfer models (with

small probabilities of sub-additive and super-multiplicative models; NCI 2002).

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Figure 3. ERR/Svy estimates (at the upper 99" percentile of the credibility distribution) for
female breast cancer (FBC, triangle) and for male miscellaneous cancer (M Misc, X) models,
from NCI (2002).

100.0 7
—t-— FBC, Exp age=15

—<~ M Misc, Exp age=15
—4A- ‘FBC, Exp age=20
—>< 'M Misc, Exp age=20
- -& - FBC, Exp age>=30

- -< - M Misc, Exp age>=30

10.0

Upper 99th percentile of ERR/Sv

SN
4 ye
a SAE SR Sk
T gene Cy Oey rey
OK
pe aD Cn ao
4.0 ttt ttt tt tt ttt ttt
25 35 45 55 65

Age at diagnosis

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Table 4. Cancer models to be used in calculation of probability of causation. Derivation of
NIOSH-IREP models is described in Section II-B. Abbreviations. MN (malignant
neoplasm), CIS (carcinoma in situ), NUB (neoplasm of uncertain behavior), NUN (neoplasm
of unspecified nature).

Primary neoplasm ICD-9 code NIOSH-IREP model for
calculating PC

Malignant neoplasm (MN) of lip, oral | 140-149 Oral cavity and pharynx

cavity and pharynx

MN of esophagus 150 Esophagus

MN of stomach 151 Stomach

MN of small intestine 152 All digestive

MN of colon 153 Colon

MN of rectum and anus 154 Rectum

MN of liver 155.0, 155.2 Liver

MN of gall bladder and bile ducts 155.1, 156 Gall bladder

MN of pancreas 157 Pancreas

MN of retroperitoneum and 158 All digestive

peritoneum

MN of other digestive 159 All digestive

MN of nasal cavities, middle ear, and | 160 Other respiratory

sinuses

MN of larynx 161 Other respiratory

MN of trachea, bronchus and lung 162 Lung

MN of pleura 163 Other respiratory

MN of thymus, heart and mediastinum | 164 Other respiratory

MN of other respiratory organs 165 Other respiratory

MN of bone 170 Bone

MN of connective tissue 171 Connective tissue

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Table 1. Radiation exposure types in NIOSH-IREP

Exposure type | Energy range Typical exposure scenario

Radon (lung All Exposure occurs near large sources of radium-bearing material such as the
cancer only) K-65 material at Fernald, or storage of radium in drums.

Electron > 14 keV Exposure typically results from processing and/or handling of fission
(source other products, such as Sr-90, or activation products, such as Co-60. Exposure
than tritium) can also result from uranium handling or processing operations.

Electron Epimax = 14 keV_ | Exposure typically occurs around tritium production facilities such as
(tritium) Savannah River and Mound, but can also result from nuclear reactor

operations or nuclear weapons assembly or research.

Photon <30 keV Low-energy x rays from transuranic isotopes such as plutonium.

Photon 30-250 keV Medium-energy photons are typically encountered from scatter of higher
energy photons. These photons can also result from gamma emissions of
certain transuranic isotopes such as americium, and are the primary energy
found in early stereoscopic x rays.

Photon >250 keV High-energy photons are the most common of the three categories listed.
These are typically encountered from work with the nuclear fuel cycle
from fuel manufacturing, reactor operations, spent nuclear fuel processing,
decontamination and decommissioning activities and waste monitoring
and storage.

Neutron <10 keV Low-energy neutrons exposures include thermal neutrons commonly
found around nuclear reactors.

Neutron 10-100 keV Intermediate-energy neutron exposure can occur around nuclear reactors
as neutrons are moderated from high energy to thermal energies.

Neutron 100 keV-2 MeV | Neutron exposure typically encountered during the operation of a nuclear
(fission) reactor. This energy of neutron exposure can also be encountered from
work with californium neutron sources.

Neutron 2-20 MeV Reactions between alpha particles from materials such as plutonium or
polonium and light materials such as beryllium resulting the production of
neutrons. These reactions are commonly called («,n) reactions, This
range also includes 14 MeV neutrons from fusion reactions.

Neutron >20 MeV Exposure to neutrons greater than 20 MeV can result from work around
accelerators.
Alpha All Primary exposure hazard is internal radiation following the inhalation or

ingestion of an alpha emitting radionuclides such as plutonium, uranium,
americium, polonium, actinium, and thorium.

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to the appropriate weighting to use for various values (including less than one), for low-
dose, chronic photon exposures, and to the incorporation of uncertainty associated with the

quadratic term of the dose-response relationship for leukemia.

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than one (i.¢., a supralinear effect at low doses). This distribution, more similar to that used by the U.S.
EPA (USEPA 1999), and the recent report by Grogan and colleagues (Grogan et al. 2000), is also the
basis for the revised NIOSH-IREP (Fig. 4a). To make the DDREF distribution consistent for breast
and thyroid cancers, NCI has added a small probability of supralinear effects at low doses (i.e., a
DDREF of less than one; Fig. 4b). This has also been adopted for use in NIOSH-IREP.

The uncertainty distribution used in both NCI’s and NIOSH’s IREP is consistent with the large
body of laboratory studies that demonstrate a reduced effect with dose protraction for most cancers
(IARC 2000, pp 301-304; UNSCEAR 2000a, pp 116-119), together with the latest analysis of the
Japanese atomic bomb survivors, which suggests no reduction (and possibly, an enhancement) of
carcinogenic effects at low doses, This DDREF distribution is used for chronic exposures, and is
invoked for acute exposures below 0.2 Sv, according to the probability distribution used in NCI’s
original IREP methodology (NCI 2000).

It should be noted that at present IREP (both NCI and NIOSH versions) assumes the
quadratic term in the leukemia dose-response relationship is fixed. Ideally, this term should have some
uncertainty associated with it (this was also mentioned by the NAS panel reviewing the draft NCI-

IREP); however, it is not clear what that uncertainty distribution should be.

E. Radiation (type) effectiveness factors (REFs)
The REF distributions used in IREP vary for each different type of radiation (Tables 5A, 5B,

and 5C). The assumptions underlying these distributions are detailed in Kocher et al. (2002). In

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Table 4 (continued). Cancer models to be used in calculation of probability of causation.
Derivation of NIOSH-IREP models is described in Section II-B. Abbreviations: MN
(malignant neoplasm), CIS (carcinoma in situ), NUB (neoplasm of uncertain behavior),
NUM (neoplasm of unspecified nature).

Primary neoplasm ICD-9 code NIOSH-IREP model for
calculating PC
CIS of larynx and other respiratory 231.0, 231.8, Other respiratory
231.9
CIS of lung 231.1, 231.2 Lung
CIS of skin 232 Malignant melanoma AND non-
melanoma skin
CIS of breast 233.0 Breast
CIS of cervix uteri or other and 233.1, 233.2 Female genitalia, less ovary
unspecified parts of uterus
CIS of other and unspecified female 233.3 Female genitalia, less ovary AND
genital organs Ovary
CIS of prostate, penis or other and 233.4 All male genitalia
unspecified male genital organs
CIS of bladder 233.7 Bladder
CIS of other and unspecified urinary | 233.9 Urinary organs less bladder
organs
CIS of eye 234.0 Eye
CIS of other and unspecified sites 234.8, 234.9 Other and ill-defined sites
Neoplasm of uncertain behavior (NUB)| 235.0, 235.1 Oral cavity and pharynx
of salivary gland, lip, oral cavity or
pharynx
NUB of stomach 235.2 Stomach
NUB of colon 235.2 Colon
NUB of rectum and anus 235.2 Rectum

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C. Cancers excluded from NIOSH-IREP
1. Chronic lymphocytic leukemia (ICD-9 204.1).

No dose-response model was developed for chronic lymphocytic leukemia (CLL) by
either the NIH Working Group (NIH 1985) or the NCI/CDC working group to update these
tables (NCI 2000). This is because no elevation of CLL incidence was observed among
Japanese atomic bomb survivors (Preston et al 1994). Because CLL is very rare among non-
Western populations (implying, therefore, that the power to detect small excess relative risks is
poor in the atomic bomb survivors study), it is necessary to evaluate the relationship observed
between radiation and CLL in other populations. No association of radiation exposure with
CLL was observed among 14,000 British ankylosing spondylitis patients treated with x rays (a
total of 2 CLL deaths; Darby et al. 1987). No elevation of CLL risk has been observed
among U.S., Canadian and European women exposed to radiation during treatment for uterine
cancer (a total of 57 CLL deaths; Curtis et al. 1994), nor has a relationship been observed in a
large study of over 124,000 nuclear workers in the U.K. (Muirhead et al. 1999). Finally, no
relationship was observed between extemal radiation dose and CLL in the first combined
international nuclear workers study (a total of 27 CLL deaths; Cardis et al 1995). Studies of
people exposed to internal sources of radiation have also not shown increased risks of CLL.
For example, no increased risk was found for CLL among patients in Denmark exposed to

Thorotrast, a “’Th-containing contrast medium (Andersson et al. 1993, [ARC 2001)

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5. Connective tissue cancer, eye cancer, other endocrine cancer, and other and ill-defined
sites

There is very little specific information about the radiogenicity of the following cancer
groups:

(1) connective and other soft tissue cancers (ICD-9 171),

(2) cancer of the eye (ICD-9 190),

(3) cancer of the endocrine glands other than thyroid (ICD-9 194), or

(4) cancers of other, ill-defined and unspecified sites (ICD-9 196 and 199).

The NCI-IREP program contains a set of “miscellaneous” ERR per Sv coefficients
derived from analysis of these and a few other sites, namely bone cancer and male breast
cancer. To implement probability of causation models for the four groups above, the
miscellaneous-site ERR per Sv model was applied to the background cancer incidence rates
(U.S. and Japan) for each of the four groupings defined above, using data from Parkin et al.
(1997). Thus, there are four additional models within NIOSH-IREP, for each of the four

groupings described above (Table 2, 4).

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Figure 1. U.S. White and African-American cancer excess incidence ratio (calculated as
higher rate divided by lower rate, minus 1), for cancers showing heterogeneity by race (data
from Parkin et al. 1997). Bars extending to the left indicate cancers that have higher
incidence rates among African-Americans, and bars extending to the right indicate cancers
with higher incidence rates among whites.

Leukemia
Multiple myeloma
Non-Hodgkin's |
Thyroid |

Brain

Bladder

Testis

Prostate

Ovary

Uterus

Cervix 0 Females

Breast mTM Males
Melanoma

Bone

Lung
Pancreas
Liver

Small intestine
Stomach
Esophagus
Mouth

Tongue

- T , T r r

3 6 9 12 15 18
Cancer Excess Incidence Ratio

wo
°

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change, reflecting a preference for the use of epidemiological data to estimate low-dose effects, is the
latest analyses of the Japanese atomic bomb survivor data (Pierce and Preston 2000), upon which the
majority of IREP models are based. This analysis strongly supports a linear over a sublinear (e.g.,
linear-quadratic) model, even within the lowest dose categories. The A-bomb survivor study (the
epidemiological study deemed most informative in the development of other risk modifiers, such as
gender and age at exposure) does not support the use of a DDREF of much larger than one, for low-
dose acute exposures. [The DDREF in NCI-IREP is phased-in at acute doses lower than 0.2 Sv — well
above levels found to be linear in studies of incidence (Pierce and Preston 2000) and mortality (Pierce
et al. 1996) in the A-bomb survivor cohort].

The recent strong evidence for a linear (or, more weakly, for a supralinear) dose-response
relationship for all solid incident cancers in the dose range of 0.05 to 0.1 Sv in the A-bomb study is
made more compelling because it avoids the potential biases for which the finding in the mortality series
has been criticized. On the other hand, there is substantial evidence from animal studies supporting a
DDREF of greater than two (summarized on pp. 60-66 of NCRP 1997 and on p 23 in BEIR V 1990)
for low-LET exposures. Moreover, most expert committees, including the NCRP, the ICRP, and
UNSCEAR, recommend a DDREF of about 2 (NCRP 1997, p 66; ICRP 1991b; UNSCEAR
20000, p 358).

However, in light of the new analysis of cancer incidence in low-dose ranges of the Japanese
A-bomb study referenced above, the NCI has shifted the DDREF distribution for all solid cancers in

IREP to more heavily weight a DDREF of one, and to include a small probability for a DDREF of less

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Table 2 (continued). Cancer sites as source for excess relative risk (ERR) per Sv coefficients
for risk models in NIOSH-IREP, and Cancer group to which model should be applied.

Cancer models in NIOSH-IREP Cancer site used as ICD-9 codes of
source of ERR/SV background rates
(IcD-9)
Ovary (183) 183 183
Female genitalia less ovary (179-182, 184)} 179-182, 184 179-182, 184
All male genitalia (185-187) 185-187 185-187
Bladder (188) 188 188
Kidney and other urinary organs (188-189) 188-189 189
Eye (190) 170, 171, 175, 190, 190
194, 195
Nervous system (191, 192) 191, 192 191, 192
Thyroid (193) 193 193
Other endocrine glands (194) 170, 171, 175, 190, 194
194, 195
Other and ill-defined sites (195, 199) 170, 171, 175, 190, 195
194, 195
Lymphoma and Multiple Myeloma (200- | 200-203 200-203
203)
Leukemia, less chronic lymphocytic 204-208, less 204.1 204-208, less 204.1
leukemia (204-208, less 204.1)
Acute lymphocytic leukemia (204.0) 204.0 204.0
Acute myelogenous leukemia (205.0) 205.0 205.0
Chronic myelogenous leukemia (205.1) | 205.1 205.1

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3. Malignant melanoma

The association between malignant melanoma and radiation is not clear. Few studies
have been conducted with sufficient power to detect increases in the relative risk of melanoma.
This problem is exacerbated by the fact that background incidence rates are very low for some
populations in which radiation-related risks have been evaluated. For example, the point
estimate of radiation excess relative risk among atomic bomb survivors is high, but with a wide
confidence interval, due to the very small number of cases (Ron et al. 1998). No significant
excess of malignant melanoma was observed among the primarily African and Asian cohort of
children exposed to radiation for the treatment of tinea capitis (scalp ringworm) in Israel (Ron et
al. 1991). However, a small study of Israeli children exposed to x rays during cardiac
catheterization showed elevated incidence of malignant melanoma (Modan et al. 2000). The
radiation-related relative risk point estimate for melanomas was very similar to that for non-
melanoma skin cancer in an irradiated North American population; however, the melanoma
estimate was based on sparse data (Hildreth et al. 1985).

Most studies of DOE workers have shown no association between malignant
melanoma and radiation exposure. However, early studies of workers at the Lawrence
Livermore National Laboratory showed elevated incidence of malignant melanoma compared
to the adjacent community, although risk was not associated with recorded doses to ionizing
radiation (Austin et al. 1981). This finding has been attributed by some to potentially increased

surveillance among this population, and to important related factors, such as skin pigmentation

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al. 1992, 1993). An inverse dose-rate effect has also been observed in studies of radon-exposed
workers (Hornung and Meinhardt 1987, Xuan et al. 1993, Tomasek et al. 1994); however, it has not
been observed at doses below approximately 50 working level months (Lubin et al. 1995), nor has it
been adopted in expert panel assessments of low-dose radon risk (NAS/NRC 1999). Such an inverse
dose-rate effect was not incorporated for models of lung cancer risk from radon exposure, because it is

implicitly included in the form of the dose-response relationship for that exposure.

F. Definitions of smoking categories for lung cancer claims

The NCI IREP program includes an adjustment to the probability of causation estimate for
primary lung cancer, based on an assumed submultiplicative relationship between smoking and lung
cancer (NCI 2000, pp. 48-50). There are seven smoking categories included in the NCI model (Table
6). No adjustments were made to this model for NIOSH-IREP; however, the definitions of the cancer
categories require clarification for use under EEOICPA. The first clarification needed is that only
cigarette smoking history is considered. This is a result of precedent established in the first NIH
Radioepidemiological Tables (NIH 1985), based on the strong, unambiguous, and quantifiable
relationship between cigarette smoking and lung cancer (Baron and Rohan 1996). In addition, all
smoking categories are defined as of the date of the primary cancer diagnosis. Lastly, additional
clarification is given for the definitions of “never smoker” and “former smoker.” For EEOICPA, a
“never smoker” is defined as a person who has smoked fewer than 100 cigarettes throughout his or her

lifetime (prior to cancer diagnosis). Most epidemiologic studies define the “never smoker” category as

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NIOSH-IREP technical documentation June 18, 2002

summary, the approach used to estimate the REF for each type of radiation was to review the relevant
literature comparing the REF for the specific exposure type as compared to high-dose, high-energy
photon radiation (i.e., the same exposure type as experienced by the Japanese atomic bomb survivors).
Evidence from neoplastic endpoints was preferentially considered.

The REF was assumed to be unity for photons of energy greater than 250 keV, as this is the
primary exposure in the Japanese atomic bomb survivors studies, upon which the majority of the risk
estimates are based. Two sets of distributions, having an increased REF compared to >250 keV
photons, were established for photons of lower energy, based on reviews of the relevant radiobiological
literature. The REF distributions assumed for electrons are also based on values obtained from review
of the relevant literature (Kocher et al. 2002; Table 5A). For alpha radiation, the estimated REF for
chronic alpha exposure compared to low-dose-rate, low-LET exposure was also much greater than
one (Kocher et al. 2002, Table 5B).

For neutrons, the REF distribution was estimated first for fission neutrons (those of energy
between 100 keV and 2 MeV). For neutrons of higher or lower energy, an REF reduction factor was
applied (Table 5, ICRP 1991b). The neutron REFs include an adjustment for a possible inverse dose-
rate relationship for chronic exposures (Kocher et al. 2002; Table 5C). This factor increases the effect
of a given dose for a chronic relative to an acute exposure. A direct adjustment is also made within
NIOSH-IREP for a possible inverse dose rate relationship for all alpha radiation exposure except
radon (as discussed below). The inverse dose-rate phenomenon has been observed for many in vitro

and animal studies, but it is thought to apply to a rather narrow range of LET and total dose (Brenner et

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In addition to these individual studies, most expert committees have listed CLL as a
cancer that appears non-radiogenic. The BEIR V Committee report (NAS/NRC 1990)
excluded CLL from the group of leukemias for which risk models were produced, based on the
lack of an association found among the studies reviewed. The UNSCEAR 2000 report states
that CLL appears to be non-inducible by radiation exposure (UNSCEAR 2000c, p. 308). In
summary, chronic lymphocytic leukemia is strongly associated with attained age. No evidence
has been found in published studies that ionizing radiation is associated with increased risk of
CLL. This approach will be revisited in future versions of NIOSH-IREP, as new scientific

information becomes available.

D. Dose and dose-rate effectiveness factors

As indicated in Section I of this report, changes in the DDREF and REF distributions adopted
in the final NCI program were used in NIOSH-IREP. These changes include substantial modifications
of the uncertainty distributions for the REF, described in detail in the accompanying document (Kocher
et al. 2002).

For DDREF, the NCI-IREP program has modified an uncertainty distribution used by Grogan
et al. (2000), p. 6-23, for low linear energy transfer (LET) radiation (NCI 2002). The uncertainty
distribution is similar to that recommended in NCRP (1997), except that it is discrete, more heavily
weights a DDREF of one, and it incorporates a small probability of a DDREF less than one (i.e., it

allows the possibility of an inverse dose-rate effect for low-LET radiation). The justification for this

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NIOSH-IREP technical documentation June 18, 2002

Figure 4. Draft and final DDREF distribution used in NIOSH-IREP for (a) all solid cancers
except breast and thyroid and (b) breast and thyroid cancer.

(@) 0.40

0.35 ¢- ---------~-~~----------~-~~-------------
0.30 4. -------~----— ~~ gue — - gy - - --- -----------

0.25 ¢- ----~---------- -- 4 ----------------
0.20 + ---~------ --4 - - 4 ----------------
0.15 f+ ---------- ~~ --- ----------------
0.10 4---~~------~ -- a --- ---ye -----------
0.05 4 ------——-- -- 3 --@ ------__------
000 a UU

0.50 0.70 1.00 1.50 2.00 3.00 4.00 §.00
DDREF, Solid cancers (except breast and thyroid)

Probability

® 0.40

Probability

0.50 0.70 1.00 1.50 2.00 3.00 4,00 5.00
DDREF, Breast and thyroid cancers

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Table 4 (continued). Cancer models to be used in calculation of probability of causation.
Derivation of NIOSH-IREP models is described in Section II-B. Abbreviations: NM
(malignant neoplasm), CIS (carcinoma in situ), NUB (neoplasm of uncertain behavior),
NUN (neoplasm of unspecified nature.

Primary neoplasm ICD-9 code NIOSH-IREP model for
calculating PC

Malignant melanoma 172 Malignant melanoma

Basal cell carcinoma of skin 173 Non-melanoma skin-Basal cell

Other (non-basal cell, non-melanoma) | 173 Non-melanoma skin-Squamous cell

carcinoma of skin

MN of breast 174, 175 Breast

MN of uterus or uterine cervix

179, 180, 182

Female genitalia less ovary

leukemia

MN of ovary 183 Ovary

MN of other female genital 181, 184 Female genitalia less ovary

MN of male genital 185-187 All male genitalia

MN of urinary bladder 188 Bladder

MN of kidney and other urinary organs | 189 Urinary organs less bladder

MN of eye 190 Eye

MN of brain and other nervous system | 191, 192 Nervous system

MN of thyroid gland 193 Thyroid

MN of other endocrine glands 194 Other endocrine glands

MN of other and ill-defined sites 195 Other and ill-defined sites
Non-Hodgkin’s lymphoma and other | 200-202 Lymphoma and muitiple myeloma
lymphoid tissue, Hodgkin’s disease

Multiple myeloma and other 203 Lymphoma and multiple myeloma
immunoproliferative diseases

Acute and unspecified lymphocytic 204.0, 204.9 Acute lymphoid leukemia

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4. Male breast cancer

Breast cancer is extremely rare among men: the age-adjusted incidence is 0.7 per
100,000 among white males, compared to 90.7 per 100,000 for white females in the U.S.
(Parkin et al. 1997). As a result, this cancer is very difficult to study directly in men, and little
is known about risk factors for male breast cancer, with the exception of Klinefelter syndrome,
a known major risk factor (Hultborn et al. 1997). A few sporadic cases among men given
medical radiation treatment have been reported (Greene et al. 1983, Olsson and Ranstam
1988). However, the following lines of evidence (summarized in Henderson et al. 1996)
suggest that male breast cancer may have similar hormonally-related cancer promotion risk
factors as female breast cancer: 1) Breast cancer in males, as in females, increases greatly with
age 2) Male breast cancer is associated with overweight in early adulthood, a finding that is
true for post-menopausal women as well. 3) Gynecomastia (a factor related to excess
estrogen) is a risk factor for breast cancer in men 4) Evidence from mathematical modeling of
breast tissue aging in men and women suggests that differences in predicted tissue
concentrations of estrogen are sufficient to explain the differences in breast cancer incidence
among the sexes (Casagrande et al. 1988, Bernstein et al. 1989, Thomas et al. 1992, Hsing et
al. 1998). Hormonally-related risk factors have been found to interact multiplicatively with
radiation, in studies of female Japanese atomic bomb survivors (Land et al. 1994, NCI 2002).
Thus, the excess relative risk of radiation-induced male breast cancer (applied to the

background rates of males) may be similar to that of female breast cancer. An alternative

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NIOSH-IREP technical documentation June 18, 2002

separately; Table 7). Therefore, for secondary cancers with unknown primary site, this table will be
consulted to select likely primary sites, which will each then be evaluated using NIOSH-IREP.

Ifno primary or secondary cancer site is specified (i.e., the cancer is identified as ICD-9 199,
with no secondary cancer site specified), then the model for “Other and ill-defined sites” should be used

(Table 2, 4),

IV. Limitations of NIOSH-IREP

As stated previously, the basis of NIOSH-IREP is the set of methods and models developed by
the National Cancer Institute, which updated the 1985 Radioepidemiological Tables developed by a
National Institutes of Health working group. The National Research Council (NAS/NRC 2000)
identified some limitations to the methods used in the first draft of NCI-IREP (NCI 2000), many of
which were addressed by NCI in the version that is the basis of NIOSH-IREP (NCI 2002). The
revised NCI report (NCI 2002) considers the current IREP software to be an interim product that may
require substantial revision after the publication of the consensus of the BEIR VII committee.

Several limitations existing in the revised NCI methods could not be addressed in NIOSH-IREP,
due to the very short time frame established by EEOICPA. The following list describes some of these
limitations, It is anticipated that these and other limitations will be remedied in future versions of
NIOSH-IREP.

A. For EEOICPA, the ideal source population from which to develop risk estimates for

probability of causation calculation is the DOE workforce itself, particularly for exposures

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NIOSH-IREP technical documentation June 18, 2002

Cc.

Large changes in cancer incidence over time exist for many cancers (e.g., breast, lung,
prostate); however, the background rates have been fixed at a single point in time (usually,
1990). Failing to incorporate these changes could lead to an overestimation or
underestimation of a claimant’s probability of causation.

Some of the source models for risk coefficients have unquantified uncertainty related to the
latency between exposure and cancer incidence. For example, the excess relative risk of
leukemia between 2 and 5 years following exposure is unknown, because the follow-up
time for the Japanese atomic bomb survivors began 5 years after the exposure. Excess
relative risks between 2 and 5 years after exposure may be different than those 5 or more
years after exposure. This limitation is less likely to exist for other cancer types because of
the generally longer latency for most cancers.

The assumed form of interaction between UV radiation exposure or susceptibility (as
reflected by racial and ethnic differences in background skin cancer risk) and radiation
exposure is highly uncertain, and has not been evaluated formally through a thorough
assessment (or meta-analysis) of the relevant literature. Similarly, formal evaluations of the
risk factor interactions for many cancers (e.g., breast and stomach) could further elucidate
the appropriate form of risk transfer between the Japanese and U.S. populations.

The uncertainty distribution of the adjustment factor for low-dose, low dose-rate exposure
(i.e., the DDREF) used in NCI’s and NIOSH’s IREP currently has a large influence on the

calculated probability of causation values. This factor merits further attention with respect

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NIOSH-IREP technical documentation June 18, 2002

Both the basal cell carcinoma and the miscellaneous cancer models have higher
ERR/Sv estimates than the squamous cell carcinoma model (NCI 2002). Of these two, the
basal cell carcinoma model produces higher ERR/Sv estimates for men at all combinations of
age at exposure and attained age, and for women at younger ages of exposure (Fig. 2). At
ages of exposure above about 35, the miscellaneous cancer model produces slightly greater
ERR/Sv estimates (but these are both quite low, considering typical exposure patterns at DOE
facilities). Therefore, it would in general be most favorable to the claimant to use the basal cell
carcinoma model to provide excess relative risk estimates for malignant melanoma. These
estimates should be applied to the background incidence rates for malignant melanoma in Japan
and the U.S., and the same risk transfer model as for other skin cancers, as discussed earlier
(e., the distribution favoring neither the additive nor the multiplicative interaction model).

For these reasons, the ERR per Sv estimates for basal cell carcinoma were used to
evaluate probability of causation for malignant melanoma. The sources of background
incidence rates used in NIOSH-IREP for malignant melanoma of the skin are the same as for
other cancers: Japanese incidence data were obtained from Parkin et al. (1997), and U.S. rates
(race- and ethnicity-specific) were obtained from the U.S. Surveillance Epidemiology and End

Results (SEER) program.

Page 23 of 73


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NIOSH-IREP technical documentation June 18, 2002

and sunlight exposure patterns, which were not considered in the initial study (Hiatt et al. 1986,
Moore et al. 1997). Other recent studies have concluded that, while surveillance bias may
have partially contributed to the observed excess in malignant melanoma, an association with
employment exposures including ionizing radiation persists after adjusting for confounding
factors (Hiatt et al. 1993, Schwartzbaum et al. 1994, Austin and Reynolds 1997). Among
other nuclear worker cohorts, skin cancer mortality (predominantly malignant melanoma) was
found to be associated with external ionizing radiation dose in the U.K. National Registry of
Radiation Workers cohort (Carpenter et al. 1994), although that finding was not significant in a
later study of that cohort (Muirhead et al. 1999),

Direct quantitative estimates of radiation risk for malignant melanoma are not generally
available. The risk estimates from the Japanese atomic bomb survivor data have very wide
confidence intervals, as they are based on only ten cases; however, they are consistent with the
rates for basal cell carcinoma (Ron et al. 1998). There is great need for future studies of
malignant melanoma in radiation-exposed populations, in order to better estimate risk
coefficients for this cancer. However, in the absence of direct information, three reasonable
potential sources of risk coefficients are those developed in IREP for non-melanoma skin
cancer (one model each for basal cell and squamous cell carcinoma) and the miscellaneous site
cancer model. Using the model producing the highest ERR/Sv risk coefficients would be
consistent with HHS policy decisions about selecting the most claimant-favorable among

equally-valid alternatives in determining probability of causation in EEOICPA.

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NIOSH-IREP technical documentation

June 18, 2002

Table 4 (continued). Cancer models to be used in calculation of probability of causation.
Derivation of NIOSH-IREP models is described in Section II-B. Abbreviations: MN
(malignant neoplasm), CIS (carcinoma in situ), NUB (neoplasm of uncertain behavior),
NUM (neoplasm of unspecified nature).

digestive organs

Primary neoplasm ICD-9 code NIOSH-IREP model for
calculating PC

Subacute and other (not chronic) 204.2, 204.8 Leukemia, less CLL

lymphoid leukemia

Acute and unspecified myelogenous 205.0, 205.9 Leukemia, less CLL AND Acute

leukemia myeloid leukemia

Chronic myelogenous leukemia 205.1 Leukemia, less CLL AND Chronic
myeloid leukemia

Subacute myelogenous leukemia, 205.2, 205.3, Leukemia, less CLL

myeloid sarcoma, and other myeloid 205.8

leukemia

Monocytic leukemia, other specified 206, 207 Leukemia, less CLL

leukemia

Acute leukemia of unspecified cell type] 208.0 Leukemia, less CLL AND Acute
lymphoid leukemia, AND Acute
myeloid leukemia

Chronic leukemia of unspecified cell | 208.1 Leukemia, less CLL AND Chronic

type myeloid leukemia

Carcinoma in situ (CIS) of lip, oral 230.0 Oral cavity and pharynx

cavity and pharynx

CIS of esophagus 230.1 Esophagus

CIS of stomach 230.2 Stomach

CIS of colon 230.3 Colon

CIS of rectum, anal canal, and anus 230.4, 230.5, Rectum

230.6
CIS of liver and biliary system 230.8 Liver
CIS of other and unspecified intestine, | 230.7, 230.9 All digestive

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NIOSH-IREP technical documentation June 18, 2002

never, rare or highly infrequent smokers (e.g., Rogot and Murray 1980, McLaughlin et al. 1995). This
quantitative classification is currently in use by the CDC in several national surveys of smoking behavior
(Anonymous 1994). A “former smoker” is an individual who ceased smoking cigarettes at least five
years before the date of primary lung cancer diagnosis. This definition is adopted from the original NIH
radioepidemiological tables, and is based on the observation that lung cancer background risks are not

reduced for the first five years following smoking cessation (Rogot and Murray 1980).

III. Cancer model selection

The model to be used in NIOSH-IREP for each primary cancer is given in Table 4. For some
cancers (e.g., certain leukemias) more than one IREP model will be employed. In this case, the model
producing the highest probability of causation at the upper 99% credibility limit is to be used as a basis
for the compensation decision,

IREP models do not specifically include cancers as defined in their early stages: carcinoma in situ
(CIS). These neoplasms are becoming more frequently diagnosed, as the use of cancer screening
tools, such as mammography, has increased in the general population. Thus, many cancers of epithelial
origin are now being detected before they have spread to the basement membrane of the affected
tissue. The risk factors and treatment for CIS are frequently similar to those for malignant neoplasms.
While controversial, there is growing evidence that CIS represents the earliest detectable phase of
malignancy (Correa 1996, Kerlikowske et al. 1997, Grippo and Sandgren 2000), and they have been

included in some evaluations of radiation-related cancer risks (Ron et al. 1998). It is uncertain what

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NIOSH-IREP technical documentation June 18, 2002

to alpha radiation. Despite the finding of excess cancers among some DOE populations, at
present it is difficult to use these findings in a quantitative risk assessment, because of
uncertainties about confounding exposures (like chemical exposures), complex patterns and
timings of exposure and disparate findings among different populations. It is likely that
current research studies underway and future research will provide a better basis for
quantitative risk assessment using data that relates directly to the DOE workforce,
particularly for cancers found to be weakly associated with radiation exposure in the
Japanese atomic bomb survivor cohort (or not at all associated, such as chronic
lymphocytic leukemia).

B. Consideration of the appropriateness of various methods of incorporating the modification
of cancer risk from radiation exposure by time-dependent factors such as age at exposure,
time since exposure and attained age. The NCI-IREP modeling approach, in particular,
requires further evaluation in future versions of NIOSH-IREP, as there are alternative ways
of modeling the data. For example, a recent re-analysis of the A-bomb survivors suggests
that, excluding the hormonally-related cancers (such as breast and thyroid), no variation by
age-at-exposure is indicated for remaining cancers after accounting for attained age (Pierce
and Mendelsohn 1996). Models that provide equivalent fit to the source data (e.g., the
Japanese atomic bomb survivor cohort) could produce quite different estimates of assigned
share for a given claimant; however, the current NCI models (adopted for NIOSH-IREP)

use a fixed modeling approach to incorporate these factors.

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